Data mining analysis of the prognostic impact of N6-methyladenosine regulators in patients with endometrial adenocarcinoma.
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ABSTRACT:
SUBMITTER: Zhai J
PROVIDER: S-EPMC8210566 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The significance of N6-methyladenosine (m6A) RNA modifications in the progression of breast cancer (BC) has been recognised. However, their potential role and mechanism of action in the tumour microenvironment (TME) and immune response has not been demonstrated. Thus, the role of m6A regulators and their downstream target gene components in BC remain to be explored. In this study, we used a series of bioinformatics methods and experiments to conduct exploratory research on the possible role of m6A regulators in BC. First, two regulatory modes of immune activation and inactivation were determined by tumour classification. The TME, immune cell infiltration, and gene set variation analysis results confirmed the reliability of this pattern. The prognostic model of the m6A regulator was established by the least absolute shrinkage and selection operator and univariate and multivariate Cox analyses, with the two regulators most closely related to survival verified by real-time quantitative reverse transcription polymerase chain reaction. Next, the prognostic m6A regulator identified in the model was crossed with the differential copy number of variant genes in invasive BC (IBC), and it was determined that YTHDF1 was a hub regulator. Subsequently, single-cell analysis revealed the expression patterns of m6A regulators in different IBC cell populations and found that YTHDF1 had significantly higher expression in immune-related IBC cells. Therefore, we selected the intersection of the BC differential expression gene set and the differential expression gene set of a cell line with knocked-down YTHDF1 in literature to identify downstream target genes of YTHDF1, in which we found IFI6, EIR, and SPTBN1. A polymerase chain reaction was conducted to verify the results. Finally, we confirmed the role of YTHDF1 as a potential prognostic biomarker through pan-cancer analysis. Furthermore, our findings revealed that YTHDF1 can serve as a new molecular marker for BC immunotherapy.
| S-EPMC8786853 | biostudies-literature
Project description:Objective: N6-methyladenosine (m6A) modification is involved in modulating various biological processes in human cancers. But the implication of m6A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m6A regulators in LUAD. Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m6A regulators using ConsensusClusterPlus package. Overall survival (OS), activation of signaling pathways and tumor immunity (immune/stromal score, tumor purity, expression of HLA and immune checkpoints, and immune cell infiltration) were compared between m6A modification patterns. The m6A-related genes between patterns were identified and prognostic m6A-related genes were imported into LASSO-cox regression analysis. The m6A risk score was developed and its prognostic implication was evaluated and externally verified in the GSE30219 and GSE72094 dataset. Furthermore, a nomogram that contained independent prognostic indicators was established, followed by external verification. Results: Two m6A modification patterns were clustered across LUAD based on the expression similarity of the m6A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m6A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m6A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m6A risk score displayed a prominent survival advantage. After incorporating independent clinical features, we developed the prognostic nomogram that exhibited high predictive accuracy and the best clinical net benefit for OS. Conclusion: Collectively, our study may provide a clinically useful tool for precise prognostic management and optimization of immunotherapeutic strategies for LUAD patients.
| S-EPMC8697852 | biostudies-literature
Project description:N6-methyladenosine (m6A) RNA methylation is dynamically and reversibly regulated by methyltransferases, binding proteins, and demethylases. The restoration of m6A to adenosine could result in demethylation modifications. Abnormalities in m6A epigenetic modifications in cancer are of increasing interest in recent years. According to the progression and prognostic performance of m6A epigenetic modifications in gastric adenocarcinoma (STAD), this study comprehensively analyzed the m6A modification patterns of gastric adenocarcinoma specimens in The Cancer Genome Atlas (TCGA) database based on 20 m6A regulators. Here, we found that 20 m6A RNA methylation regulators were high-expressed in gastric adenocarcinoma. m6A RNA methylation regulators were closely associated with pT staging of gastric cancer. Based on such findings, we developed a prognostic model using four m6A RNA methylation regulators (IGF2BP1, RBM15, FTO, ALKBH5), and the FTO was confirmed as an independent prognostic marker.
| S-EPMC8921461 | biostudies-literature
Project description:To assess the impact of CD133 expression on the prognosis of endometrioid endometrial carcinoma (EEC). We retrospectively assessed CD133 expression in tissue microarray of 116 surgically treated FIGO I-III EEC. Tumors with ≥10% of CD133-expressing cells were considered CD133-positive (CD133+). On the basis of CD133 expression, clinical and pathological parameters, progression-free survival (PFS) and overall survival (OS) were evaluated. Of the EEC studied 85.2% showed CD133-expressing cells. Only 61% (n = 66) of EEC presented ≥10% of CD133 expressing cells and were considered CD133+. The mean OS for CD133+ tumour patients was 161 months (95% CI, 154-168) as compared with 146 months (95% CI, 123-160) for those with CD133- tumors (p = 0.012). The mean PFS for CD133+ tumour was 159 months (95% CI, 149-168) as compared with 147 months (95% CI, 132-161) in those with a CD133-tumour (p = 0.014). CD133+ tumours were less likely to have vascular invasion (p = 0.010) and more likely to be well differentiated (p = 0.034). C133+ tumours predicted favorable OS and PFS of EEC patients, with a Hazard Ratio 4.731 (95% CI, 1.251-17.89; p = 0.022). CD133+ tumor status correlates with favorable prognosis of EEC. Our findings are in agreement with studies addressing brain and colorectal tumours.
| S-EPMC5550511 | biostudies-other
Project description:Aberrant regulation of m6A mRNA modification can lead to changes in gene expression, thus contributing to tumorigenesis in several types of solid tumors. In this study, by integrating analyses of m6A methylation and mRNA expression, we identified 84 m6A-regulated mRNAs in lung adenocarcinoma (LUAD). Although the m6A methylation levels of total RNA in LUAD patient tumor tissue were reduced, the majority (75.2%) of m6A-regulated mRNAs were hypermethylated. The m6A-hypermethylated mRNAs were mainly enriched in terms related to transcription factor activity. We established a 10-m6A-regulated-mRNA signature score system through least absolute shrinkage and selection operator Cox regression analysis, with its predictive value validated by Kaplan-Meier curve and time-dependent receiver operating characteristic curves. RFXAP and KHDRBS2 from the signature also exhibited an independent prognostic value. The co-expression and interaction network analyses demonstrated the strong correlation between m6A regulators and the genes in the signature, further supporting the results of the m6A methylation modification patterns. These findings highlight the potential utility of integrating multi-omics data (m6A methylation level and mRNA expression) to accurately obtain potential prognostic biomarkers, which may provide important insights into developing novel and effective therapies for LUAD.
| S-EPMC8377381 | biostudies-literature
Project description:N6-methyladenosine [m(6)A/m6A] methylation is one of the most common RNA modifications in eukaryotic cell mRNA and plays an important regulatory role in mRNA metabolism, splicing, translocation, stability, and translation. Previous studies have demonstrated that the m6A modification is highly associated with tumor cell proliferation, migration, and invasion. In the present study, five m6A regulatory factors have been revealed, namely heterogeneous nuclear ribonucleoprotein A2/B1(HNRNPA2B1), heterogeneous nuclear ribonucleoprotein C (HNRNPC), Vir like m6A methyltransferase associated protein (KIAA1429/VIRMA), RNA binding motif protein 15 (RBM15) and methyltransferase like 3 (METTL3), which are closely related to the overall survival (OS) of patients with lung adenocarcinoma (LUAD). These five m6A regulatory factors exhibited potential prognostic value for the 1, 3, and 5-years survival outcomes of LUAD patients. Our findings revealed that several signaling pathways, such as cell cycle, DNA replication, RNA degradation, RNA polymerase, nucleotide excision repair and basal transcription factors, are activated in the high-risk group of LUAD patients.
| S-EPMC7902930 | biostudies-literature
Project description:Background: N6-methyladenosine (m6A) RNA methylation is dynamically and reversibly regulated by methyl-transferases ("writers"), binding proteins ("readers"), and demethylases ("erasers"). The m6A is restored to adenosine and thus to achieve demethylation modification. The abnormality of m6A epigenetic modification in cancer has been increasingly attended. However, we are rarely aware of its diagnostic, progressive and prognostic performance in lung adenocarcinoma (LUAD). Methods and Results: The expression of 13 widely reported m6A RNA regulators in LUAD and normal samples were systematically analyzed. There were 12 m6A RNA methylation genes displaying aberrant expressions, and an 11-gene diagnostic score model was finally built (Diagnostic score =0.033*KIAA1429+0.116*HNRNPC+0.115*RBM15-0.067* METTL3-0.048*ZC3H13-0.221*WTAP+0.213*YTHDF1-0.132*YTHDC1-0.135* FTO+0.078*YTHDF2+0.014*ALKBH5). Receiver operating characteristic (ROC) analysis was performed to demonstrate superiority of the diagnostic score model (Area under the curve (AUC) was 0.996 of training cohort, P<0.0001; AUC was 0.971 of one validation cohort-GSE75037, P<0.0001; AUC was 0.878 of another validation cohort-GSE63459, P<0.0001). In both training and validation cohorts, YTHDC2 was associated with tumor stage (P<0.01), while HNRNPC was up expressed in progressed tumor (P<0.05). Besides, WTAP, RBM15, KIAA1429, YTHDF1, and YTHDF2 were all up expressed for TP53 mutation. Furthermore, using least absolute shrinkage and selection operator (lasso) regression analysis, a ten-gene risk score model was built. Risk score=0.169*ALKBH5-0.159*FTO+0.581*HNRNPC-0.348* YTHDF2-0.265*YTHDF1-0.123*YTHDC2+0.434*RBM15+0.143*KIAA1429-0.200*WTAP-0.310*METTL3. There existed correlation between the risk score and TNM stage (P<0.01), lymph node stage (P<0.05), gender (P<0.05), living status (P<0.001). Univariate and multivariate Cox regression analyses of relevant clinicopathological characters and the risk score revealed risk score was an independent risk factor of lung adenocarcinoma (HR: 2.181, 95%CI (1.594-2.984), P<0.001). Finally, a nomogram was built to facilitate clinicians to predict outcome. Conclusions: m6A epigenetic modification took part in the progression, and provided auxiliary diagnosis and prognosis of LUAD.
| S-EPMC7211177 | biostudies-literature
Project description:N6-methyladenosine (m6A) regulators play an important role in tumorigenesis; however, their role in multiple myeloma (MM) remains unknown. This study aimed to create an m6A RNA regulators prognostic signature for MM patients. We integrated data from the Multiple Myeloma Research Foundation CoMMpass Study and the Genotype-Tissue Expression database to analyze gene expression profiles of 21 m6A regulators. Consistent clustering analysis was used to identify the clusters of patients with MM having different clinical outcomes. Gene distribution was analyzed using principal component analysis. Next, we generated an mRNA gene signature of m6A regulators using a multivariate logistic regression model with least absolute shrinkage and selection operator. The expressions of m6A regulators, except FMR1, were significantly different in MM samples compared with those in normal samples. The KIAA1429, HNRNPC, FTO, and WTAP expression levels were dramatically downregulated in tumor samples, whereas those of other signatures were remarkably upregulated. Three clusters of patients with MM were identified, and significant differences were found in terms of overall survival (p = .024). A prognostic two-gene signature (KIAA1429 and HNRNPA2B1) was constructed, which had a good prognostic significance using the ROC method (AUC = 0.792). Moreover, the risk score correlated with the infiltration immune cells. In addition, KEGG pathway analysis showed that 16 pathways were dramatically enriched. The m6A signature might be a novel biomarker for predicting the prognosis of patients with MM (p = .002). Our study is the first to explore the potential application value of m6A in MM. These findings may enhance the understanding of the functional organization of m6A in MM and provide new insights into the treatment of MM patients.
| S-EPMC10115423 | biostudies-literature
Project description:Purpose: This study aims to reveal the relationship between RNA N6-methyladenosine (m6A) regulators and tumor immune microenvironment (TME) in breast cancer, and to establish a risk model for predicting the occurrence and development of tumors. Patients and methods: In the present study, we respectively downloaded the transcriptome dataset of breast cancer from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database to analyze the mutation characteristics of m6A regulators and their expression profile in different clinicopathological groups. Then we used the weighted correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and cox regression to construct a risk prediction model based on m6A-associated hub genes. In addition, Immune infiltration analysis and gene set enrichment analysis (GSEA) was used to evaluate the immune cell context and the enriched gene sets among the subgroups. Results: Compared with adjacent normal tissue, differentially expressed 24 m6A regulators were identified in breast cancer. According to the expression features of m6A regulators above, we established two subgroups of breast cancer, which were also surprisingly distinguished by the feature of the immune microenvironment. The Model based on modification patterns of m6A regulators could predict the patient's T stage and evaluate their prognosis. Besides, the low m6aRiskscore group presents an immune-activated phenotype as well as a lower tumor mutation load, and its 5-years survival rate was 90.5%, while that of the high m6ariskscore group was only 74.1%. Finally, the cohort confirmed that age (p < 0.001) and m6aRiskscore (p < 0.001) are both risk factors for breast cancer in the multivariate regression. Conclusion: The m6A regulators play an important role in the regulation of breast tumor immune microenvironment and is helpful to provide guidance for clinical immunotherapy.
| S-EPMC8793540 | biostudies-literature
Project description:As the most prevalent internal eukaryotic modification, N6-methyladenosine (m6A) is installed by methyltransferases, removed by demethylases, and recognized by readers. However, there are few studies on the role of m6A in clear cell renal cell carcinoma (ccRCC). In this study, we researched the RNA-seq transcriptome data of ccRCC in the TCGA dataset and used bioinformatics analyses to detect the relationship between m6A RNA methylation regulators and ccRCC. First, we compared the expression of 18 m6A RNA methylation regulators in ccRCC patients and normal tissues. Then, data from ccRCC patients were divided into two clusters by consensus clustering. LASSO Cox regression analysis was used to build a risk signature to predict the prognosis of patients with ccRCC. An ROC curve, univariate Cox regression analysis, and multivariate Cox regression analysis were used to verify this risk signature's predictive ability. Then, we internally validated this signature by random sampling. Finally, we explored the role of the genes in the signature in some common pathways. Gene distribution between the two subgroups was different; cluster 2 was gender-related and had a worse prognosis. IGF2BP3, IGF2BP2, HNRNPA2B1, and METTL14 were chosen to build the risk signature. The overall survival of the high- and low-risk groups was significantly different (p = 7.47e - 12). The ROC curve also indicated that the risk signature had a decent predictive significance (AUC = 0.72). These results imply that the risk signature has a potential value for ccRCC treatment.
| S-EPMC7895564 | biostudies-literature